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group of Dr. Mario dos Reis, as part of a BBSRC project on development of Bayesian methods to analyse large genomic datasets. We seek a highly motivated individual with relevant background in statistics
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thermodynamics, statistical physics, computational physics, and particle levitation, but the critical requirements are a proven ability to learn fast, to think creatively and to work in a team. Within King’s, you
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health services research, epidemiology, statistics, psychology or public health. 2. Good interpersonal skills 3. Attention to detail 4. Proficiency in IT (Word, Excel, database use) 5
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, conduct statistical analyses and interpretation, prepare scientific manuscripts and disseminate results at scientific meetings. To operate independently with regular mentoring as part of a strong
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a high level of proficiency with computer software related to laboratory research, data presentation and statistical evaluation, as well as the ability to organise a varied workload between research
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Post-Doctoral Research Associate/ Post-Doctoral Research Fellow in the Department of Health Services
health services research, epidemiology, statistics, psychology or public health. 2. Good interpersonal skills 3. Attention to detail 4. Proficiency in IT (Word, Excel, database use) 5
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Knowledge & experience of LC-MS based metabolomics using Sciex Zeno TOF MS Knowledge & experience of LC-MS based lipidomics Knowledge & experience of computational and statistical procedures for analysing
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31st July 2025. The successful candidate will harness genetic, multi-omic and lifestyle/clinical information from large-scale population-based and clinical cohorts, and use cutting-edge statistical
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. Solid expertise in research methods, including experience with coding and data management in common statistical programming languages (e.g. Stata, R, and/or Python). Desirable criteria 4. A good
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enthusiastic about scientific research. Expertise in molecular biology, cell biology and statistical and bioinformatics analysis of large datasets is essential. Experience with multi-omics profiling and signal